CN109493928B - Patient data screening method, system, equipment and storage medium based on condition tree - Google Patents
Patient data screening method, system, equipment and storage medium based on condition tree Download PDFInfo
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- CN109493928B CN109493928B CN201811332222.8A CN201811332222A CN109493928B CN 109493928 B CN109493928 B CN 109493928B CN 201811332222 A CN201811332222 A CN 201811332222A CN 109493928 B CN109493928 B CN 109493928B
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Abstract
The invention provides a patient data screening method, a system, equipment and a storage medium based on a condition tree, wherein the method comprises the steps of collecting patient data; acquiring screening conditions set by a user and an incidence relation among the screening conditions; generating a condition node of the condition tree according to each screening condition, generating a relation node of the condition tree according to each incidence relation, and establishing the incidence relation between each relation node and the condition node; counting the number of patients of each node; displaying a condition tree, displaying the screening conditions at the condition nodes, displaying the types of the relation nodes at the relation nodes, connecting the associated condition nodes and the relation nodes, and displaying the corresponding number of patients at each condition node and each relation node. By adopting the scheme of the invention, the user can more visually and clearly see the combination relation of the screening conditions, and the screened number is displayed on each node, so that the relation of the screened number among the specific conditions can be conveniently compared.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a patient data screening method, a patient data screening system, patient data screening equipment and a storage medium based on a condition tree.
Background
The research objects of doctor scientific research projects are patient populations meeting a certain condition or a combination of a plurality of specific conditions, so that the accurate screening of patients meeting the conditions based on the conditions is an extremely key premise in clinical scientific research projects. The relationship among the conditions and the number of the patients screened based on the conditions are displayed more visually in a graph form, so that doctors can more quickly acquire the number information of the patients meeting the conditions, the method is very helpful for scientific research work and data analysis of the doctors, and the method is a very important technology in scientific research projects.
However, most of the display modes in the prior art are displayed in a way of tiling condition input boxes (fields, relationships, values), and only the number of patients screened by all condition combinations is displayed, and the combination relationship of a plurality of conditions cannot be seen more intuitively. For example, if the 5 conditions are displayed in a tiled mode, the relationship among the conditions, which condition is the same as the condition, and which condition is the same as the condition, can not be visually compared with the number of patients screened out by each condition node, and therefore, the method is not easy to operate, consumes time, and reduces the scientific research efficiency.
Disclosure of Invention
Aiming at the problems in the prior art and the search requirements of various scenes in actual medical scientific research projects, the invention aims to provide a patient data screening method, a system, equipment and a storage medium based on a condition tree, which can enable a user to more visually and clearly see the combination relationship of screening conditions, and meanwhile, each node has the number of screened people displayed, so that the relation of the number of screened people among specific conditions can be conveniently compared.
The embodiment of the invention provides a patient data screening method based on a condition tree, which comprises the following steps:
collecting patient data, respectively counting the patient data meeting each statistical condition, and storing the patient data in a patient database, wherein each statistical condition comprises an attribute and an attribute value for statistics;
acquiring screening conditions set by a user and an incidence relation among the screening conditions, wherein the screening conditions comprise attributes and attribute values for screening;
generating a condition node of the condition tree according to each screening condition, generating a relation node of the condition tree according to each incidence relation, and establishing the incidence relation between each relation node and the condition node;
searching patient data corresponding to each screening condition according to the attribute and the attribute value of each screening condition, and adding the number of the patients in the searched patient data to the corresponding condition node;
counting the patient data of the condition node associated with each relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the corresponding relationship node;
displaying the condition tree, displaying the screening condition at each condition node, displaying the type of the relation node at each relation node, connecting the associated condition node and relation node, and displaying the corresponding number of patients at each condition node and relation node.
Optionally, the searching for the patient data corresponding to each of the screening conditions according to the attribute and the attribute value in each of the screening conditions includes the following steps:
judging whether statistical conditions identical to the attributes and attribute values of the screening conditions exist in the patient database or not;
if so, taking the patient data with the same statistical condition as the patient data of the screening condition;
if the attribute value of the selected condition is not the same as the attribute value of the selected condition, searching for the statistical condition with the attribute value of the selected condition being crossed or contained in the patient database, and combining the searched patient data of the statistical condition to obtain the patient data of the selected condition.
Optionally, the type of the relationship node includes a relationship node and/or a relationship node, and the statistics of the patient data satisfying the association relationship according to the type of each relationship node includes the following steps:
if the type of the relation node is the same as that of the relation node, searching patient data with the same patient in the patient data of the condition node associated with the relation node, and taking the patient data with the same patient as the patient data meeting the association relation;
and if the type of the relationship node is the relationship node, integrating the patient data of the condition node associated with the relationship node, and removing the repeated patient data of the patient in the integrated patient data to serve as the patient data meeting the association relationship.
Optionally, the method further comprises the following steps:
if the type switching operation of the relationship node of the user is acquired, the type of the relationship node is changed;
if the type of the relationship node is changed from the relationship node to the relationship node, integrating the patient data of the condition node associated with the relationship node, removing repeated patient data of the patient in the integrated patient data as the patient data meeting the changed type, and updating the number of the patients in the relationship node according to the patient data meeting the changed type;
and if the type of the relation node is changed from or the relation node to the relation node, searching patient data with the same patient in the patient data of the condition node associated with the relation node, taking the patient data with the same patient as the patient data meeting the changed type, and updating the number of the patients of the relation node according to the patient data meeting the changed type.
Optionally, the method further comprises the following steps:
if the screening condition adding operation of the user is obtained, a new condition node is generated;
establishing a corresponding relation between a new condition node and a relation node according to the relation node associated with the screening condition adding operation;
searching patient data corresponding to the new screening condition according to the attribute and the attribute value of the new screening condition, and adding the number of the patients in the searched patient data to the corresponding condition node;
and re-counting the patient data of the relationship node associated with the new screening condition, and updating the number of patients of the relationship node according to the re-counted patient data meeting the association relationship.
Optionally, the method further comprises the following steps:
if the screening condition deleting operation of the user is acquired, deleting the screening condition and determining a relation node associated with the screening condition;
and re-counting the patient data of the relationship node associated with the deleted screening condition, and updating the number of patients of the relationship node according to the re-counted patient data meeting the association relationship.
Optionally, the method further comprises the following steps:
if the incidence relation adding operation of the user is acquired, generating a new relation node;
judging whether the incidence relation between the user and the condition node exists in the incidence relation adding operation of the user, if so, establishing the incidence relation between a new relation node and the condition node, and if not, prompting the user to input a new screening condition;
and counting the patient data of the condition node associated with the new relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the new relationship node.
Optionally, the method further comprises the following steps:
if the incidence relation deleting operation of the user is obtained, deleting the relation node corresponding to the deleted incidence relation, and determining the screening node related to the relation node;
and judging whether the associated screening node has an association relation with other relation nodes, if so, retaining the screening node, and if not, deleting the screening node.
Optionally, the method further comprises the following steps:
creating a dimension node at each relationship node, wherein the types of the dimension nodes comprise the same patient, the same medical record and the same time node;
and if the dimension node selection operation of the user is acquired, judging the dimension node type selected by the user, screening the patient data meeting the relationship node according to the dimension node type, and taking the screened patient data as the patient data of the relationship node.
The embodiment of the invention also provides a patient data screening system based on the condition tree, which is applied to the patient data screening method based on the condition tree, and the system comprises:
the data statistics module is used for collecting patient data, respectively counting the patient data meeting each statistical condition, and storing the patient data in a patient database, wherein each statistical condition comprises an attribute and an attribute value for statistics;
the system comprises a condition acquisition module, a condition selection module and a condition selection module, wherein the condition acquisition module is used for acquiring screening conditions set by a user and an incidence relation among the screening conditions, and the screening conditions comprise attributes and attribute values for screening;
the node generation module is used for generating a condition node of the condition tree according to each screening condition, generating a relation node of the condition tree according to each incidence relation and establishing the incidence relation between each relation node and the condition node;
the node counting module is used for searching the patient data corresponding to each screening condition according to the attribute and the attribute value of each screening condition and adding the number of the patients in the searched patient data to the corresponding condition node; counting the patient data of the condition node associated with each relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the corresponding relationship node;
and the condition tree display module is used for displaying the condition tree, displaying the screening condition at each condition node, displaying the type of the relation node at each relation node, connecting the associated condition node and the relation node, and displaying the corresponding number of the patients at each condition node and each relation node.
The embodiment of the invention also provides patient data screening equipment based on the condition tree, which comprises:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the conditional tree based patient data screening method via execution of the executable instructions.
Embodiments of the present invention also provide a computer-readable storage medium for storing a program, which when executed, implements the steps of the conditional tree-based patient data screening method.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
The patient data screening method, the patient data screening system, the patient data screening equipment and the patient data screening storage medium based on the condition tree have the following advantages:
the invention provides a patient data screening method for medical storage and drainage and a condition tree display mode, wherein screening conditions are connected by lines, so that a user can more visually and clearly see the combination relationship of the screening conditions, meanwhile, the number of the screened conditions is displayed on each node, the relationship of the number of people screened among specific conditions is conveniently compared, the conditions can be combined by using a 'sum' or a 'or', and the invention provides a technology for searching the condition tree in three dimensions of 'same patient, same medical record and same time node', provides great flexible support, and is convenient for a doctor to check and search related patient data.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method of patient data screening based on a conditional tree according to an embodiment of the present invention;
FIGS. 2-6 are schematic structural diagrams of a condition tree after patient data screening according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a conditional tree based patient data screening system according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a patient data screening apparatus based on a conditional tree in accordance with an embodiment of the present invention;
fig. 9 is a schematic diagram of a computer-readable storage medium according to an embodiment of the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
As shown in fig. 1, in order to solve the above technical problem, an embodiment of the present invention provides a patient data screening method based on a condition tree, including the following steps:
s100: collecting patient data, respectively counting the patient data meeting each statistical condition, and storing the patient data in a patient database, wherein each statistical condition comprises an attribute and an attribute value for statistics; the attribute can be a plurality of predefined attributes, such as sex, diagnosis department, nasal symptom, ABO blood type and the like, each attribute corresponds to at least one attribute value, and for the attribute value of each attribute, statistics can be carried out to obtain patient data meeting the statistical condition; correspondingly, the patient data may include a plurality of attributes of a patient and attribute values of the plurality of attributes;
s200: acquiring screening conditions set by a user and an incidence relation among the screening conditions, wherein the screening conditions comprise attributes and attribute values for screening; for example, the user sets one screening condition as ABO blood type a, the other screening condition as gender male, and the association relationship between the two is yes, then the number of patients meeting the two screening conditions needs to be counted;
s300: generating a condition node of the condition tree according to each screening condition, generating a relation node of the condition tree according to each incidence relation, and establishing the incidence relation between each relation node and the condition node;
s400: searching patient data corresponding to each screening condition according to the attribute and the attribute value of each screening condition, and adding the number of the patients in the searched patient data to the corresponding condition node;
s500: counting the patient data of the condition node associated with each relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the corresponding relationship node;
s600: displaying the condition tree, displaying the screening condition at each condition node, displaying the type of the relation node at each relation node, connecting the associated condition node and relation node, and displaying the corresponding number of patients at each condition node and relation node.
The above-mentioned labels of each step are only for identifying and distinguishing each step, and in practical application, the order among the above-mentioned steps can be adjusted without following the above-mentioned order, for example, after the condition tree is displayed first, then the patient number of each node is obtained by statistics, then the patient number is displayed on the condition tree, etc., all of which are within the protection scope of the present invention.
FIGS. 2-6 illustrate the structure of a condition tree after patient data screening in accordance with an embodiment of the present invention. The technical scheme of the invention is specifically described below with reference to fig. 2 to 6, as shown in the figure, the number of people screened under each node (combination condition) is shown, and each condition and each combination of conditions can display the number of people like a funnel, so that the method is very intuitive.
In this embodiment, the searching for the patient data corresponding to each of the screening conditions according to the attribute and the attribute value in the screening condition includes the following steps:
judging whether statistical conditions identical to the attributes and attribute values of the screening conditions exist in the patient database or not;
if so, taking the patient data with the same statistical condition as the patient data of the screening condition; for example, one of the screening conditions is also gender male, and when one of the statistical conditions is found to be gender male, the patient data with the statistical condition of gender male can be used as the patient data of the screening condition;
if the attribute value of the selected condition is not the same as the attribute value of the selected condition, searching for the statistical condition with the attribute value of the selected condition being crossed or contained in the patient database, and combining the searched patient data of the statistical condition to obtain the patient data of the selected condition.
For example, the patient data of the screening condition may be obtained by removing the patient data of the first statistical condition from the patient data of the second statistical condition when one screening condition is that the visit time is between 3/1/2018 and 2/1/2018, and only one statistical condition is that the visit time is before 2/1/2018, and one statistical condition is that the visit time is before 3/1/2018.
In this embodiment, the type of the relationship node includes and relationship node and or relationship node, i.e. the association relationship may be and or both; the method for counting the patient data meeting the incidence relation according to the type of each relation node comprises the following steps:
if the type of the relation node is the same as that of the relation node, searching patient data with the same patient in the patient data of the condition node associated with the relation node, and taking the patient data with the same patient as the patient data meeting the association relation;
and if the type of the relationship node is the relationship node, integrating the patient data of the condition node associated with the relationship node, and removing the repeated patient data of the patient in the integrated patient data to serve as the patient data meeting the association relationship.
As shown in fig. 2, there is a switch button at the lower right of the relation node "and", and the user clicks the switch button, the type switch of the relation node can be realized. In this embodiment, the logical relationship between conditions defaults to and the switch relationship can be clicked on at will, thereby supporting more patient data search scenarios.
Specifically, in this embodiment, the method for screening patient data based on the conditional tree further includes the following steps:
if the type switching operation of the relationship node of the user is acquired, the type of the relationship node is changed;
if the type of the relationship node is changed from the relationship node to the relationship node, integrating the patient data of the condition node associated with the relationship node, removing repeated patient data of the patient in the integrated patient data as the patient data meeting the changed type, and updating the number of the patients in the relationship node according to the patient data meeting the changed type;
and if the type of the relation node is changed from or the relation node to the relation node, searching patient data with the same patient in the patient data of the condition node associated with the relation node, taking the patient data with the same patient as the patient data meeting the changed type, and updating the number of the patients of the relation node according to the patient data meeting the changed type.
As shown in fig. 3, there is a plus sign below the "and" relationship node, and a condition node associated with the relationship node can be added by clicking the plus sign, that is, a filtering condition is added. Specifically, in this embodiment, the method for screening patient data based on the conditional tree further includes the following steps:
if the screening condition adding operation of the user is obtained, a new condition node is generated;
establishing a corresponding relation between a new condition node and a relation node according to the relation node associated with the screening condition adding operation;
searching patient data corresponding to the new screening condition according to the attribute and the attribute value of the new screening condition, and adding the number of the patients in the searched patient data to the corresponding condition node;
and re-counting the patient data of the relationship node associated with the new screening condition, and updating the number of patients of the relationship node according to the re-counted patient data meeting the association relationship. That is, the screening condition of the condition node is combined with other screening conditions wired on the relationship node, and in an alternative relationship.
Further, as shown in fig. 3, a delete button is further disposed above the relation node "and can be clicked to delete the relation node, as shown in fig. 4, a delete button and an add button are further disposed above the condition node" nationality equals to han nationality ", and the condition node or the add condition node can be deleted.
Thus, in this embodiment, the method for conditional tree-based patient data screening further comprises the steps of:
if the screening condition deleting operation of the user is acquired, deleting the screening condition and determining a relation node associated with the screening condition;
and re-counting the patient data of the relationship node associated with the deleted screening condition, and updating the number of patients of the relationship node according to the re-counted patient data meeting the association relationship.
Further, the patient data screening method based on the condition tree further comprises the following steps:
if the incidence relation adding operation of the user is acquired, generating a new relation node;
judging whether the incidence relation between the user and the condition node exists in the incidence relation adding operation of the user, if so, establishing the incidence relation between a new relation node and the condition node, and if not, prompting the user to input a new screening condition;
and counting the patient data of the condition node associated with the new relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the new relationship node.
Further, the patient data screening method based on the condition tree further comprises the following steps:
if the incidence relation deleting operation of the user is obtained, deleting the relation node corresponding to the deleted incidence relation, and determining the screening node related to the relation node;
and judging whether the associated screening node has an association relation with other relation nodes, if so, retaining the screening node, and if not, deleting the screening node.
As shown in fig. 4, there are editing buttons above the condition node "nationality equals to Han nationality", and each specific filtering condition is shown in the form of text description, and an input box and a selection box appear to edit the condition when modified and added, as shown in fig. 5. The input boxes may appear to be of different types depending on the data type (text, time, value, etc.) of the selected field.
Further, as shown in fig. 6, the conditional tree of the present invention can also switch dimensions. In the embodiment, three dimensions of ' same patient, same medical record and same time node ' are provided, and the selection of patients meeting the field condition combination in the medical record data of the same time can be realized by switching the dimensions of ' same medical record ', ' same latitude ' and ' same time ', and meanwhile, any combination of the field condition combinations in the dimensions of ' same medical record ', ' same latitude.
Therefore, the patient data screening method based on the condition tree of the embodiment further comprises the following steps:
creating a dimension node at each relationship node, wherein the types of the dimension nodes comprise the same patient, the same medical record and the same time node;
and if the dimension node selection operation of the user is acquired, judging the dimension node type selected by the user, screening the patient data meeting the relationship node according to the dimension node type, and taking the screened patient data as the patient data of the relationship node.
As shown in fig. 7, an embodiment of the present invention further provides a patient data screening system based on a conditional tree, which is applied to the patient data screening method based on a conditional tree, and the system includes:
a data statistics module 100, configured to collect patient data, respectively count patient data meeting various statistics conditions, and store the patient data in a patient database, where each statistics condition includes an attribute and an attribute value used for statistics;
the condition acquisition module 200 is configured to acquire a screening condition set by a user and an association relationship between the screening conditions, where the screening condition includes an attribute and an attribute value used for screening;
a node generating module 300, configured to generate a condition node of the condition tree according to each screening condition, generate a relationship node of the condition tree according to each association relationship, and establish an association relationship between each relationship node and the condition node;
the node counting module 400 is configured to search for patient data corresponding to each screening condition according to the attribute and the attribute value of each screening condition, and add the number of patients in the searched patient data to the corresponding condition node; counting the patient data of the condition node associated with each relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the corresponding relationship node;
a condition tree display module 500, configured to display the condition tree, display the screening condition at each condition node, display the type of the relationship node at each relationship node, connect the associated condition node and relationship node, and display the corresponding number of patients at each condition node and relationship node.
The embodiment of the invention also provides patient data screening equipment based on the condition tree, which comprises a processor; a memory having stored therein executable instructions of the processor; wherein the processor is configured to perform the steps of the conditional tree based patient data screening method via execution of the executable instructions.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" platform.
An electronic device 600 according to this embodiment of the invention is described below with reference to fig. 8. The electronic device 600 shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 8, the electronic device 600 is embodied in the form of a general purpose computing device. The combination of the electronic device 600 may include, but is not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting different platform combinations (including memory unit 620 and processing unit 610), a display unit 640, etc.
Wherein the storage unit stores program code executable by the processing unit 610 to cause the processing unit 610 to perform steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of the present specification. For example, the processing unit 610 may perform the steps as shown in fig. 1.
The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.
The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.
Embodiments of the present invention also provide a computer-readable storage medium for storing a program, which when executed, implements the steps of the conditional tree-based patient data screening method. In some possible embodiments, aspects of the present invention may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of this specification, when the program product is run on the terminal device.
Referring to fig. 9, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, compared with the prior art, the patient data screening method, system, device and storage medium based on the condition tree provided by the invention have the following advantages:
the invention provides a patient data screening method for medical storage and drainage and a condition tree display mode, wherein screening conditions are connected by lines, so that a user can more visually and clearly see the combination relationship of the screening conditions, meanwhile, the number of the screened conditions is displayed on each node, the relationship of the number of people screened among specific conditions is conveniently compared, the conditions can be combined by using a 'sum' or a 'or', and the invention provides a technology for searching the condition tree in three dimensions of 'same patient, same medical record and same time node', provides great flexible support, and is convenient for a doctor to check and search related patient data.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (12)
1. A method for conditional tree-based screening of patient data, the method comprising the steps of:
collecting patient data, respectively counting the patient data meeting each statistical condition, and storing the patient data in a patient database, wherein each statistical condition comprises an attribute and an attribute value for statistics;
acquiring screening conditions set by a user and an incidence relation among the screening conditions, wherein the screening conditions comprise attributes and attribute values for screening;
generating a condition node of the condition tree according to each screening condition, generating a relation node of the condition tree according to each incidence relation, and establishing the incidence relation between each relation node and the condition node;
searching patient data corresponding to each screening condition according to the attribute and the attribute value of each screening condition, and adding the number of the patients in the searched patient data to the corresponding condition node;
counting the patient data of the condition node associated with each relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the corresponding relationship node;
displaying the condition tree, displaying the screening condition at each condition node, displaying the type of the relation node at each relation node, connecting the associated condition node and the relation node, and displaying the corresponding number of patients at each condition node and each relation node;
the method for searching the patient data corresponding to each screening condition according to the attribute and the attribute value in each screening condition comprises the following steps:
judging whether statistical conditions identical to the attributes and attribute values of the screening conditions exist in the patient database or not;
if so, the patient data for the same statistical condition is taken as the patient data for the screening condition.
2. The conditional tree-based patient data screening method of claim 1, further comprising:
and when the statistical conditions which have the same attribute and attribute value as the screening conditions do not exist in the patient database, searching the statistical conditions which have the same attribute as the screening conditions and cross or inclusion relationship between the attribute values and the attribute values of the screening conditions in the patient database, and combining the searched patient data of the statistical conditions to obtain the patient data of the screening conditions.
3. The method for screening patient data based on conditional tree according to claim 1, wherein the type of the relationship node comprises a relationship node and/or a relationship node, and the method for counting the patient data satisfying the association relationship according to the type of each relationship node comprises the following steps:
if the type of the relation node is the same as that of the relation node, searching patient data with the same patient in the patient data of the condition node associated with the relation node, and taking the patient data with the same patient as the patient data meeting the association relation;
and if the type of the relationship node is the relationship node, integrating the patient data of the condition node associated with the relationship node, and removing the repeated patient data of the patient in the integrated patient data to serve as the patient data meeting the association relationship.
4. The conditional tree-based patient data screening method of claim 3, further comprising the steps of:
if the type switching operation of the relationship node of the user is acquired, the type of the relationship node is changed;
if the type of the relationship node is changed from the relationship node to the relationship node, integrating the patient data of the condition node associated with the relationship node, removing repeated patient data of the patient in the integrated patient data as the patient data meeting the changed type, and updating the number of the patients in the relationship node according to the patient data meeting the changed type;
and if the type of the relation node is changed from or the relation node to the relation node, searching patient data with the same patient in the patient data of the condition node associated with the relation node, taking the patient data with the same patient as the patient data meeting the changed type, and updating the number of the patients of the relation node according to the patient data meeting the changed type.
5. The conditional tree-based patient data screening method of claim 1, further comprising the steps of:
if the screening condition adding operation of the user is obtained, a new condition node is generated;
establishing a corresponding relation between a new condition node and a relation node according to the relation node associated with the screening condition adding operation;
searching patient data corresponding to the new screening condition according to the attribute and the attribute value of the new screening condition, and adding the number of the patients in the searched patient data to the corresponding condition node;
and re-counting the patient data of the relationship node associated with the new screening condition, and updating the number of patients of the relationship node according to the re-counted patient data meeting the association relationship.
6. The conditional tree-based patient data screening method of claim 1, further comprising the steps of:
if the screening condition deleting operation of the user is acquired, deleting the screening condition and determining a relation node associated with the screening condition;
and re-counting the patient data of the relationship node associated with the deleted screening condition, and updating the number of patients of the relationship node according to the re-counted patient data meeting the association relationship.
7. The conditional tree-based patient data screening method of claim 1, further comprising the steps of:
if the incidence relation adding operation of the user is acquired, generating a new relation node;
judging whether the incidence relation between the user and the condition node exists in the incidence relation adding operation of the user, if so, establishing the incidence relation between a new relation node and the condition node, and if not, prompting the user to input a new screening condition;
and counting the patient data of the condition node associated with the new relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the new relationship node.
8. The conditional tree-based patient data screening method of claim 1, further comprising the steps of:
if the incidence relation deleting operation of the user is obtained, deleting the relation node corresponding to the deleted incidence relation, and determining the screening node related to the relation node;
and judging whether the associated screening node has an association relation with other relation nodes, if so, retaining the screening node, and if not, deleting the screening node.
9. The conditional tree-based patient data screening method of claim 1, further comprising the steps of:
creating a dimension node at each relationship node, wherein the types of the dimension nodes comprise the same patient, the same medical record and the same time node;
and if the dimension node selection operation of the user is acquired, judging the dimension node type selected by the user, screening the patient data meeting the relationship node according to the dimension node type, and taking the screened patient data as the patient data of the relationship node.
10. A conditional tree-based patient data screening system applied to the conditional tree-based patient data screening method according to any one of claims 1 to 9, the system comprising:
the data statistics module is used for collecting patient data, respectively counting the patient data meeting each statistical condition, and storing the patient data in a patient database, wherein each statistical condition comprises an attribute and an attribute value for statistics;
the system comprises a condition acquisition module, a condition selection module and a condition selection module, wherein the condition acquisition module is used for acquiring screening conditions set by a user and an incidence relation among the screening conditions, and the screening conditions comprise attributes and attribute values for screening;
the node generation module is used for generating a condition node of the condition tree according to each screening condition, generating a relation node of the condition tree according to each incidence relation and establishing the incidence relation between each relation node and the condition node;
the node counting module is used for searching the patient data corresponding to each screening condition according to the attribute and the attribute value of each screening condition and adding the number of the patients in the searched patient data to the corresponding condition node; counting the patient data of the condition node associated with each relationship node, counting the patient data meeting the association relationship according to the type of each relationship node, counting the number of patients in the obtained patient data, and adding the counted number of patients to the corresponding relationship node;
and the condition tree display module is used for displaying the condition tree, displaying the screening condition at each condition node, displaying the type of the relation node at each relation node, connecting the associated condition node and the relation node, and displaying the corresponding number of the patients at each condition node and each relation node.
11. A patient data screening apparatus based on a conditional tree, comprising:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the conditional tree based patient data screening method of any of claims 1 to 9 via execution of the executable instructions.
12. A computer readable storage medium storing a program, wherein the program when executed implements the steps of the conditional tree based patient data screening method of any of claims 1 to 9.
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